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Glama

CDF Finance

by io.github.VessellTech

Insights por categoria

categories_insights
Read-only

Gasto acumulado por categoria (somando subcategorias) no mês alvo vs mês anterior, com % de variação e comparação com orçamento (se houver Budget mensal para a categoria). Sem month/year usa o mês atual e serve a versão materializada (mais rápida); com month/year calcula ao vivo. Para série de vários meses use category_history; para insights por tag (não categoria) use tags_insights; para um resumo de correlações do momento (poupança, dívida, reserva) use financial_snapshot.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoAno alvo (default ano atual)
monthNoMês alvo, 1-12 (default mês atual). Informar sem year usa o ano atual
userIdNoId do cliente a consultar (uso de planejador financeiro); omitido usa o próprio usuário autenticado

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNo
monthNo
insightsNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed4 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / month
      Added value: +{
+  "description": "Mês alvo, 1-12 (default mês atual). Informar sem year usa o ano atual",
+  "type": "number"
+}
    • addedInput schema / properties / userId
      Added value: +{
+  "description": "Id do cliente a consultar (uso de planejador financeiro); omitido usa o próprio usuário autenticado",
+  "type": "string"
+}
    • addedInput schema / properties / year
      Added value: +{
+  "description": "Ano alvo (default ano atual)",
+  "type": "number"
+}
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds meaningful behavioral context beyond annotations: it sums subcategories, compares to the previous month, conditionally includes budget comparison, defaults to the current month, and switches between materialized and live calculation. This gives the agent a solid understanding of what the tool actually does at runtime.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but efficient, front-loading the core purpose before moving to behavioral nuances and sibling alternatives. It could be slightly more scannable with separate sentences, but every clause earns its place and there is no redundant content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, the description does not need to explain return values. It covers the comparison logic, aggregation, budget conditionality, default behavior, computation modes, and alternatives, leaving no significant gap for an agent to call this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the structured schema already documents year, month, and userId well. The description adds extra value by explaining the behavioral consequence of omitting month/year (materialized fast path vs. live calculation) and clarifies that omitting year uses the current year, complementing the schema defaults.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb and resource: accumulated spend by category, compared with the previous month, including percentage change and budget comparison. It also explicitly differentiates itself from sibling tools by naming category_history, tags_insights, and financial_snapshot, so an agent can select the right tool without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit routing guidance: use category_history for multi-month series, tags_insights for tag-based insights, and financial_snapshot for correlation summaries. It also explains the materialized vs. live computation modes depending on whether month/year is supplied, which clarifies when each call mode is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All CDF Finance toolsInspect
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TDQS

A3.7/5.0
Disambiguation3/5

The tools are individually well-described and many cross-reference their closest neighbors, but the set contains several easily confused clusters: create_transaction/confirm_new_transaction, update_equity/add_equity_valuation, the invoice tools (current_invoice, next_invoice, list_pending_invoices, get_invoice), and the many analytics/projection tools. The descriptions help a careful reader, but with 81 tools an agent is likely to misselect among these overlapping surfaces.

Naming Consistency3/5

CRUD operations consistently use create_/list_/update_/delete_ plus a resource noun, and all names are snake_case. However, there is a large second group of noun-phrase analytics tools (cashflow_forecast, spending_projection, categories_insights, transport_routine) plus one-off verbs such as can_afford, pay_invoice, and validate_current_invoices, so the naming convention is mixed even though it remains readable.

Tool Count1/5

81 tools is far beyond the practical MCP tool surface and exceeds the rubric's 50+ extreme-mismatch threshold. Even if each tool maps to a real finance endpoint, the volume overwhelms an agent's context window and makes selection much harder.

Completeness4/5

The server covers the finance lifecycle extensively: accounts, cards, invoices, transactions, recurring rules, budgets, goals, debts, equities, categories, tags, cost centers, profile, projections, and insights all have working read/write paths. Minor gaps remain, such as no update/delete for tags and no direct update/delete for system-generated invoices, but agents can usually work around these.

Resources